I think this is what you want:
>>> data = [('2013-01-16', 'AAPL', 1),
('2013-01-16', 'GOOG', 1.5),
('2013-01-17', 'GOOG', 2),
('2013-01-17', 'MSFT', 4),
('2013-01-18', 'GOOG', 3),
('2013-01-18', 'MSFT', 3)]
>>> df = pd.DataFrame(data, columns=['date', 'ticker', 'value'])
>>> df
date ticker value
0 2013-01-16 AAPL 1.0
1 2013-01-16 GOOG 1.5
2 2013-01-17 GOOG 2.0
3 2013-01-17 MSFT 4.0
4 2013-01-18 GOOG 3.0
5 2013-01-18 MSFT 3.0
>>> df.pivot('date', 'ticker', 'value')
ticker AAPL GOOG MSFT
date
2013-01-16 1 1.5 NaN
2013-01-17 NaN 2.0 4
2013-01-18 NaN 3.0 3